Sampling Head
2008
 |
| No items matching your keywords were found. |
Sampling Head
Sampling , it's need and it's principles
We all know that it is a tedious task to extract information from a population. In statistical inference we draw random samples to do this job from the population from which it is drawn. The information we draw is in the form of some statistic: a sample mean, a sample S.D. etc.
The process of selecting a sample from a population is known as sampling At first a representative sample from a population is selected and then analysed.Based on this sample result statistical inferences are made about the population.
Census is a count of all elements in a population. But we generally prefer sample survey over census. Some of the reasons to prefer sample survey instead of census are the followings:
1) Cost: Sample survey is cheaper than census survey because only a part of whole population is investigated.
2) Time: Since the magnitude of operations involved in a sample survey is small, both the execution of the field work and its analysis of results can be carried out speedily.
3) Small labor: Since only a part of the whole population is investigated the method requires a small manpower. Sampling results in a greater economy of effort as a relatively small staff is required to carry out the survey and to tabulate and process the data.
4) Movement of population element : The population of fish, birds, snakes, mosquitoes etc. are large and constantly moving, being born & dying. So, instead of attempting to count all elements of such population, it is desirable to make estimates using techniques such as counting birds at a place picked at random.
5) Greater scope: There is a greater scope in sample survey than in census. In the former only a small group of skilled investigators are employed for collection of information.Althogh the cost per investigator is larger in sample survey, because of the specialized training to be imparted to those personnel, the amount of information collected by each is much larger. As such a larger geographical area can be covered & more intensive data collection can be made.
6) More precise result: Sample survey yields more precise results than census, because of the deployment of specially trained investigator & the possibility of better control and supervision over them.
7) Magnitude of error: An extra advantage of sample survey method is that the magnitude of error is known. Since it depends on the laws of probability, the magnitude of sampling errors can readily be computed.
8) Feasibility: It is seen in many cases, complete enumeration is not feasible and sample survey is the only way. For instance: In order to buy rice grains one cannot afford to examine every single grain of rice he purchases. He has to depend only on a sample, based on which he forms an idea about the quality of rice.
Principles
The two principles which determine the possibility of arriving at a valid statistical inference about the features of population are:-
1) Principle of statistical regularity: This theory is based on the theory of probability. The law of statistical regularity lays down that a moderately large number of items chosen at random from a large group are almost sure on the average to process the characteristic of large group.
The principle focuses on two factors:
a) Sample size should be large: This is because as the size of the sample increases, it becomes more representative of parent population and shows its characteristics.
b) Samples must be drawn randomly: The random sample is the one in which the elements of the population are drawn in such a way that each combination of elements has an equal probability of being selected in the sample. The selection of the sample is based on this principle can reduce the amount of efforts required in arriving at a conclusion about the characteristic of a large population.
Principle of inertia of large numbers: This is a corollary principle of statistical regularity and plays a significant role in sampling theory. This principle states that under similar conditions as the sample size get large enough; the statistical inference is likely to be more accurate and stable. For instance: If a coin is tossed a large number of times, the relative frequency of occurrence of head & tail is expected to be equal
About the Author
I(Ms Nabanita Maity)am a lecturer of a Management College in Kolkata, West Bengal, India .
A coin is tossed results in a head,a die is thrown showsup an even,the die re-thrown,tell sample of experiment?
sample means sample space is here
the sample space of the experiment consists
of 22 elements
because if a coin is tossed its outcomes are
H,T
IF result of head H, a die is thrown
H1,H2,H3,H4,H5,H6
If a die shows even number H2,H4,H6,the die
is thrown again then the sample space of
the experiment=S= H21,H22,H23 ,H24,H25,H26,
H41,H42,H43,H44,H45,H46
H61,H62,H63,H64,H65,H66
HENCE n(S)= { T,,H1,H3,H5,H21,H22,H23 ,H24,H25,H26,
H41,H42,H43,H44,H45,H46
H61,H62,H63,H64,H65,H66}= 22 ELEMENTS
Snoop Doggy Dogg - "Snoop's Upside Ya Head" sample appears from The Gap Band "Oops Upside Ya Head"
